Dynamic Water Quality Changes in the Main Stream of the Yangtze River from Combined Multi-source Remote Sensing Data

Abstract

Abstract Total nitrogen (TN) and total phosphorus (TP) are important indicators for water quality. However, although water quality with high accuracy can be obtained by traditional measurement methods, the cost is high and the area is limited. A single satellite remote sensing was used to retrieve water quality with larger scale, less bands and limited accuracy. In this paper, the inversion models of TN and TP are obtained and validated in the main stream of the Yangtze River by using multi-source remote sensing data. The accuracy of models from joint multi-source remote sensing data is higher than that from using a single satellite data. The correlation of TN joint inversion model can reach 0.80, and the root mean square error(RMSE) is about 0.5mg L-1. The correlation of TP joint inversion model can reach 0.85, and RMSE is about 0.1mg L-1. Using the models, the water quality changes are obtained and analysed in the main stream of the Yangtze River from 2019 to 2021. It is found that TN and TP in the upstream and downstream are high. In spring and autumn, the water quality is poor. The main stream of the Yangtze River mostly class III and getting better year by year. Finally, the reasons for the change of water quality are discussed with other factors. It is found that TN and TP are negatively correlated with water level, temperature and flow. The correlation between water level and water quality is higher than others and it can reach − 0.76 and − 0.64.